Abstract：The traditional similarity algorithm of collaborative filteringis modified in this paper. In order to find an optimal similarity function, the paper presents harmony search algorithm with parameters optimization to find the optimal weights vector of similarity function. To improve the speed of recommendation, harmony search algorithm is no longer used for the calculation of the recommendation after finding the optimal similarity function. The validation experiments show that the proposed algorithm improves prediction accuracy and coverage so as to provide better recommendation. And the proposed algorithm can more quickly obtain the nearest neighbor users of the target user, which can accelerate the recommended speed.
王华秋. 一种基于和声搜索的协同过滤算法研究[J]. 现代图书情报技术, 2012, (12): 79-84.
Wang Huaqiu. Research of a Collaborative Filtering Algorithm Based on Harmony Search. New Technology of Library and Information Service, 2012, (12): 79-84.
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